Measurement

Measurement

The nominal scale of measurement. Nominal data, such as the gender of an individual, cannot be ranked.

All we can do with nominal data is to say whether an individual belongs to one group or another; for instance, is male or female

The ordinal scale can be ranked.

An example of ordinal data are the educational qualifications of individuals. We can say that an individual who completed high school has a higher educational qualification than one who has not.

Much clearer about the relative distance between objects is data which is on the interval scale of measurement.

For instance, we can say that 40 degrees, the summer temperature in Los Angeles, is 28 degrees centigrade higher that the average summer temperature in Glasgow, which is said to be 12 degrees centigrade. However, it is again impossible to say that Los Angeles is twice as hot as Glasgow

The last type of data concern the ratio measurement scale.

Data belonging to the ratio scale, such as data on individual income allows us to express relationships in multiples.

So, a businessman who earns £84,000 will earn twice as much as most UK University lecturers who earn, on average £39,500.

Expressing this relationship is possible because income does have a non-arbitrary zero point as you cannot earn an income of less than zero pounds

Validity describes the extent to which an instrument actually measures what is it supposed to measure.

If a researcher distributed a survey investigating the extent of poverty only in a very rich neighborhood, her research would be less valid than if she had attempted to distribute her survey across the whole city.

Reliability, concerns the degree to which a measurement yields a consistent result.

For instance, if our poverty survey were distributed only among the residents of a student dormitory, who stay in this location for less than 2 years, it would be less reliable than if it had been distributed among long term residents.